📄 bcompgsh.cc
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/* ARPACK++ v1.0 8/1/1997 c++ interface to ARPACK code. MODULE BCompGSh.cc. Example program that illustrates how to solve a complex generalized eigenvalue problem in shift and invert mode using the ARluCompGenEig class. 1) Problem description: In this example we try to solve A*x = B*x*lambda in shift and invert mode, where A and B are derived from a finite element discretization of a 1-dimensional convection-diffusion operator (d^2u/dx^2) + rho*(du/dx) on the interval [0,1], with zero boundary conditions, using piecewise linear elements. 2) Data structure used to represent matrices A and B: {ndiagL, ndiagU, A}: matrix A data in band format. The columns of A are stored sequentially in vector A. ndiagL and ndiagU supply the lower and upper bandwidth of A, respectively. {ndiagL, ndiagU, B}: matrix B in band format. 3) Library called by this example: The LAPACK package is called by ARluCompGenEig to solve some linear systems involving (A-sigma*B). 4) Included header files: File Contents ----------- --------------------------------------------- bcmatrxb.h CompMatrixE, a function that generates matrix A in band format. bcmatrxc.h CompMatrixF, a function that generates matrix B in band format. arbnsmat.h The ARbdNonSymMatrix class definition. arbgcomp.h The ARluCompGenEig class definition. lcompsol.h The Solution function. arcomp.h The "arcomplex" (complex) type definition. 5) ARPACK Authors: Richard Lehoucq Kristyn Maschhoff Danny Sorensen Chao Yang Dept. of Computational & Applied Mathematics Rice University Houston, Texas*/#include "arcomp.h"#include "bcmatrxb.h"#include "bcmatrxc.h"#include "arbnsmat.h"#include "arbgcomp.h"#include "lcompsol.h"main(){ // Defining variables; int n; // Dimension of the problem. int ndiagL; // Lower bandwidth of A and B. int ndiagU; // Upper bandwidth of A and B. arcomplex<double> rho; // Parameter used to define A. arcomplex<double> *valA, *valB; // pointers to arrays that store // the elements of A and B. // Creating complex matrices A and B. n = 100; rho = arcomplex<double>(10.0, 0.0); CompMatrixB(n, rho, ndiagL, ndiagU, valA); ARbdNonSymMatrix<arcomplex<double> > A(n, ndiagL, ndiagU, valA); CompMatrixC(n, ndiagL, ndiagU, valB); ARbdNonSymMatrix<arcomplex<double> > B(n, ndiagL, ndiagU, valB); // Defining what we need: the four eigenvectors nearest to sigma. ARluCompGenEig<double> dprob(4L, A, B, arcomplex<double>(10.0,0.0)); // Finding eigenvalues and eigenvectors. dprob.FindEigenvectors(); // Printing solution. Solution(A, B, dprob);} // main.
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